— Partially Observable Markov Decision Processes (POMDPs) offer a powerful mathematical framework for making optimal action choices in noisy and/or uncertain environments, in par...
—This paper introduces a new algorithm for probabilistic motion planning in arbitrary, uncertain vector fields, with emphasis on high-level planning for Montgolfier´e balloons...
Michael T. Wolf, Lars Blackmore, Yoshiaki Kuwata, ...
— In the past, there has been a tremendous advance in the area of simultaneous localization and mapping (SLAM). However, there are relatively few approaches for incorporating pri...
Michael Karg, Kai M. Wurm, Cyrill Stachniss, Klaus...
— In this paper we propose a new on-line sensor self-calibration framework. The approach is to consider the sensor/robot interaction that links the sensor signal variations to th...
—We are concerned with enabling truly large scale autonomous navigation in typical human environments. To this end we describe the acquisition and modeling of large urban spaces ...
Gabe Sibley, Christopher Mei, Ian D. Reid, Paul M....